[Feature] Add Lion optimizer (#952)

docs/en/tutorials/optim_wrapper.md

@@ -243,7 +243,7 @@ As shown in the above example, `OptimWrapperDict` exports learning rates and mom
 
 ### Configure the OptimWapper in [Runner](runner.md)
 
-We first need to configure the `optimizer` for the OptimWrapper. MMEngine automatically adds all optimizers in PyTorch to the `OPTIMIZERS` registry, and users can specify the optimizers they need in the form of a `dict`. All supported optimizers in PyTorch are listed [here](https://pytorch.org/docs/stable/optim.html#algorithms). In addition, 'DAdaptAdaGrad', 'DAdaptAdam', and 'DAdaptSGD' can be used by installing [dadaptation](https://github.com/facebookresearch/dadaptation).
+We first need to configure the `optimizer` for the OptimWrapper. MMEngine automatically adds all optimizers in PyTorch to the `OPTIMIZERS` registry, and users can specify the optimizers they need in the form of a `dict`. All supported optimizers in PyTorch are listed [here](https://pytorch.org/docs/stable/optim.html#algorithms). In addition, `DAdaptAdaGrad`, `DAdaptAdam`, and `DAdaptSGD` can be used by installing [dadaptation](https://github.com/facebookresearch/dadaptation). `Lion` optimizer can used by install [lion-pytorch](https://github.com/lucidrains/lion-pytorch)。
 
 Now we take setting up a SGD OptimWrapper as an example.
 

docs/zh_cn/tutorials/optim_wrapper.md

@@ -243,7 +243,7 @@ print(optim_dict.get_momentum())  # {'gen.momentum': [0], 'disc.momentum': [0]}
 
 ### 在[执行器](./runner.md)中配置优化器封装
 
-优化器封装需要接受 `optimizer` 参数，因此我们首先需要为优化器封装配置 `optimizer`。MMEngine 会自动将 PyTorch 中的所有优化器都添加进 `OPTIMIZERS` 注册表中，用户可以用字典的形式来指定优化器，所有支持的优化器见 [PyTorch 优化器列表](https://pytorch.org/docs/stable/optim.html#algorithms)。
+优化器封装需要接受 `optimizer` 参数，因此我们首先需要为优化器封装配置 `optimizer`。MMEngine 会自动将 PyTorch 中的所有优化器都添加进 `OPTIMIZERS` 注册表中，用户可以用字典的形式来指定优化器，所有支持的优化器见 [PyTorch 优化器列表](https://pytorch.org/docs/stable/optim.html#algorithms)。另外，可以通过安装 [dadaptation](https://github.com/facebookresearch/dadaptation) 使用 `DAdaptAdaGrad`、`DAdaptAdam` 和 `DAdaptSGD` 3 个优化器。也可以通过安装 [lion-pytorch](https://github.com/lucidrains/lion-pytorch) 使用 `Lion` 优化器。
 
 以配置一个 SGD 优化器封装为例：
 

mmengine/optim/optimizer/builder.py

@@ -57,6 +57,26 @@ def register_dadaptation_optimizers() -> List[str]:
 DADAPTATION_OPTIMIZERS = register_dadaptation_optimizers()
 
 
+def register_lion_optimizers() -> List[str]:
+    """Register Lion optimizer to the ``OPTIMIZERS`` registry.
+
+    Returns:
+        List[str]: A list of registered optimizers' name.
+    """
+    optimizers = []
+    try:
+        from lion_pytorch import Lion
+    except ImportError:
+        pass
+    else:
+        OPTIMIZERS.register_module(module=Lion)
+        optimizers.append('Lion')
+    return optimizers
+
+
+LION_OPTIMIZERS = register_lion_optimizers()
+
+
 def build_optim_wrapper(model: nn.Module,
                         cfg: Union[dict, Config, ConfigDict]) -> OptimWrapper:
     """Build function of OptimWrapper.

requirements/tests.txt

@@ -1,4 +1,6 @@
 coverage
+dadaptation
+lion-pytorch
 lmdb
 parameterized
 pytest

tests/test_optim/test_optimizer/test_optimizer.py

@@ -14,6 +14,7 @@ from mmengine.optim import (OPTIM_WRAPPER_CONSTRUCTORS, OPTIMIZERS,
                             DefaultOptimWrapperConstructor, OptimWrapper,
                             build_optim_wrapper)
 from mmengine.optim.optimizer.builder import (DADAPTATION_OPTIMIZERS,
+                                              LION_OPTIMIZERS,
                                               TORCH_OPTIMIZERS)
 from mmengine.registry import build_from_cfg
 from mmengine.testing._internal import MultiProcessTestCase
@@ -34,6 +35,14 @@ def has_dadaptation() -> bool:
         return False
 
 
+def has_lion() -> bool:
+    try:
+        import lion_pytorch  # noqa: F401
+        return True
+    except ImportError:
+        return False
+
+
 class ExampleModel(nn.Module):
 
     def __init__(self):
@@ -221,6 +230,10 @@ class TestBuilder(TestCase):
         assert set(dadaptation_optimizers).issubset(
             set(DADAPTATION_OPTIMIZERS))
 
+    @unittest.skipIf(not has_lion(), 'lion-pytorch is not installed')
+    def test_lion_optimizers(self):
+        assert 'Lion' in LION_OPTIMIZERS
+
     def test_build_optimizer(self):
         # test build function without ``constructor`` and ``paramwise_cfg``
         optim_wrapper_cfg = dict(